Suchergebnisse

A shuffle. Do you experience the following? Cigarette smoke and white cheddar popcorn. It's all in my pretty little head. Crinkling paper bedsheets. Excess. A woman who swallowed a fly, leaves and steel. A polka-dot collar. Blink... Side effects are a misnomer. An artist's manifesto. Non-linear. I want to be disjointed, unformed, messy, hurting, mad. Madness is both personal and political. Through an autoethnographic series of performative poetry and prose, Loose Leaf intends to evoke encounters with some of the affects, experiences, and politics of madness and psychiatrization. It works to offer both an embodied and theoretical engagement with one form of mad performance, and to compel readers to perform a form of mad reading.

The objective of this work was to model and identify the best models for estimating the leaf area, determined by digital photos, of buckwheat (Fagopyrum esculentum Moench) of the cultivars IPR91-Baili and IPR92-Altar, as a function of length (L), width (W) or length x width product (LW) of the leaf blade. Ten uniformity trials (blank experiments) were carried out, five with IPR91-Baili cultivar and five with IPR92-Altar cultivar. The trials were performed on five sowing dates. In each trial and cultivar, expanded leaves were collected at random from the lower, middle and upper segments of the plants, totaling 1,815 leaves. In these 1,815 leaves, L and W were measured and the LW of the leaf blade was calculated, which were used as independent variables in the model. The leaf area of each leaf was determined using the digital photo method (Y), which was used as a dependent variable of the model. For each sowing date, cultivar and thirds of the plant, 80% of the leaves (1,452 leaves) were randomly separated for the generation of the models and 20% of the leaves (363 leaves) for the validation of the models of leaf area estimation as a function of linear dimensions. For buckwheat, IPR91-Baili and IPR92-Altar cultivars, the quadratic model (Ŷ = 0.5217 + 0.6581LW + 0.0004LW2, R2 = 0.9590), power model (Ŷ = 0.6809LW1.0037, R2 = 0.9587), linear model (Ŷ = 0.0653 + 0.6892LW, R2 = 0.9587) and linear model without intercept (Ŷ = 0.6907LW, R2 = 0.9587) are indicated for the estimation of leaf area determined by digital photos (Y) based on the LW of the leaf blade (x), and, preferably, the linear model without intercept can be used, due to its greater simplicity.

Abstract The leaf economics spectrum (LES) is an ecophysiological concept describing the trade-offs of leaf structural and physiological traits, and has been widely investigated on multiple scales. However, the effects of the breeding process on the LES in crops, as well as the mechanisms of the trait trade-offs underlying the LES, have not been thoroughly elucidated to date. In this study, a dataset that included leaf anatomical, biochemical, and functional traits was constructed to evaluate the trait covariations and trade-offs in domesticated species, namely rice (Oryza species). The slopes and intercepts of the major bivariate correlations of the leaf traits in rice were significantly different from the global LES dataset (Glopnet), which is based on multiple non-crop species in natural ecosystems, although the general patterns were similar. The photosynthetic traits responded differently to leaf structural and biochemical changes, and mesophyll conductance was the most sensitive to leaf nitrogen (N) status. A further analysis revealed that the relative limitation of mesophyll conductance declined with leaf N content; however, the limitation of the biochemistry increased relative to leaf N content. These findings indicate that breeding selection and high-resource agricultural environments lead crops to deviate from the leaf trait covariation in wild species, and future breeding to increase the photosynthesis of rice should primarily focus on improvement of the efficiency of photosynthetic enzymes.